Package: mevr 1.2.3
mevr: Fitting the Metastatistical Extreme Value Distribution MEVD
Extreme value analysis with the metastatistical extreme value distribution MEVD (Marani and Ignaccolo, 2015, <doi:10.1016/j.advwatres.2015.03.001>) and some of its variants. In particular, analysis can be performed with the simplified metastatistical extreme value distribution SMEV (Marra et al., 2019, <doi:10.1016/j.advwatres.2019.04.002>) and the temporal metastatistical extreme value distribution TMEV (Falkensteiner et al., 2023, <doi:10.1016/j.wace.2023.100601>). Parameters can be estimated with probability weighted moments, maximum likelihood and least squares. The data can also be left-censored prior to a fit. Density, distribution function, quantile function and random generation for the MEVD, SMEV and TMEV are included. In addition, functions for the calculation of return levels including confidence intervals are provided. For a description of use cases please see the provided references.
Authors:
mevr_1.2.3.tar.gz
mevr_1.2.3.zip(r-4.5)mevr_1.2.3.zip(r-4.4)mevr_1.2.3.zip(r-4.3)
mevr_1.2.3.tgz(r-4.4-any)mevr_1.2.3.tgz(r-4.3-any)
mevr_1.2.3.tar.gz(r-4.5-noble)mevr_1.2.3.tar.gz(r-4.4-noble)
mevr_1.2.3.tgz(r-4.4-emscripten)mevr_1.2.3.tgz(r-4.3-emscripten)
mevr.pdf |mevr.html✨
mevr/json (API)
NEWS
| # Install 'mevr' in R: |
| install.packages('mevr', repos = c('https://haraldschellander.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/haraldschellander/mevr/issues
- dailyrainfall - Daily rainfall data
Last updated 1 months agofrom:4daaabbbf5. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 03 2024 |
| R-4.5-win | OK | Nov 03 2024 |
| R-4.5-linux | OK | Nov 03 2024 |
| R-4.4-win | OK | Nov 03 2024 |
| R-4.4-mac | OK | Nov 03 2024 |
| R-4.3-win | OK | Nov 03 2024 |
| R-4.3-mac | OK | Nov 03 2024 |
Exports:censored_weibull_fitdmevdtmevevent_separationfmevfsmevftmevordinary_eventspmevpp.weibullptmevqmevqtmevreturn.levels.mevrmevweibull_tail_test
Dependencies:bamlssBHclicodacodetoolscolorspacedata.tabledistributions3doParalleldplyrEnvStatsfansifarverforeachFormulagenericsggplot2gluegtableisobanditeratorslabelinglatticelifecyclemagrittrMASSMatrixMBAmgcvmmandmunsellmvtnormnlmenortestpillarpkgconfigR6RColorBrewerRcpprlangscalesspsurvivaltibbletidyselectutf8vctrsviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Fit Weibull distribution to censored data | censored_weibull_fit |
| Daily rainfall data | dailyrainfall |
| The Metastatistical Extreme Value Distribution | dmev pmev qmev rmev |
| The non-stationary Metastatistical Extreme Value Distribution | dtmev ptmev qtmev |
| Detect Rainfall Events with Specified Separation Time (Dry Time) and Minimum Rain Threshold | event_separation |
| Fitting the Metastatistical Extreme Value Distribution (MEVD) | fmev |
| Fitting the simplified Metastatistical Extreme Value Distribution (SMEV) | fsmev |
| Fitting the temporal Metastatistical Extreme Value Distribution (TMEV) | ftmev |
| Identifies ordinary rainfall events by calculating the maximum within rainfall events defined with 'event_separation' | ordinary_events |
| Plot graphs of MEVD, SMEV or TMEV fit | plot.mevr |
| Weibull plotting position | pp.weibull |
| TMEV prediction | predict.mevr |
| Print method for object of class mevr | print.mevr |
| Return Levels for the MEVD/SMEV/TMEV extreme value distributions | return.levels.mev |
| Weibull tail test | weibull_tail_test |
